Crowd behavior can be observed among crowds of many different types of organisms, from humans to animals to cells. Crowd disasters, triggered by real or perceived dangers, are frequent, especially among gatherings of differing numbers of people. For example, over the past ten years, more than three thousand people have died in crowd disasters. Some methods for monitoring crowd behavior include detecting anomalies in crowd behavior, such as individuals avoiding a certain area or people changing directions sharply or even stampeding in response to a real or perceived danger.
Some approaches for detecting anomalies in crowd behavior rely on tracking individuals or virtual particles seeded in the area under observation and driven by the optical flow. Other approaches rely on creating and maintaining a library of normal patterns. These approaches often require high computational complexity and are not suitable for tracking large crowds in substantially real-time.